dynamic_2d_nonlinear_solve

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the burden. It discloses the output components (equilibria, Jacobian-based classification, nullclines, trajectories), giving insight into its behavior. However, it omits important computational details such as whether it uses numerical or symbolic methods, potential failure modes, or sensitivities to parameter choices.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured with clear sections for purpose, arguments, and returns. It avoids unnecessary verbosity, though it could be slightly more organized by listing each parameter. The line 'x0..y_max' is cryptic but not wordy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 14 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not fully specify the meaning of all parameters, the exact structure of the returned dict, or any edge-case behavior. An agent would need to guess at several integration and plotting settings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains eq_x, eq_y, params, and mu meaningfully, but the rest are grouped as 'x0..y_max, cantidad_trayectorias: integration and portrait settings' without detailing each. Parameters h, t0, t_fin, x_min, x_max, y_min, y_max are not individually described. With schema coverage at 0%, this leaves significant ambiguity for an agent to set values correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool solves and analyzes nonlinear 2D systems x'=f(x,y), y'=g(x,y), using a specific verb and resource. It distinguishes itself from siblings by emphasizing 'nonlinear' and the listed outputs (equilibria, Jacobian classification, nullclines, trajectories), though it doesn't explicitly contrast with alternatives like dynamic_2d_linear_solve.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied by the name and description: it is meant for nonlinear 2D systems. The phrase 'Solve and analyze the nonlinear 2D system' indicates the type of problem it addresses, but there is no explicit guidance on when not to use it or which sibling tool to choose (e.g., linear, conservative, nonhomogeneous).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.